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Spectrum occupancy models are very useful in cognitive radio designs. They can be used to increase spectrum sensing accuracy for more reliable operation, to remove spectrum sensing for higher resource usage efficiency, or to select channels for better opportunistic access, among other applications. In this survey, various spectrum occupancy models from measurement campaigns taken around the world...
Mechatronics as an interdisciplinary field, which combines knowledge from multiple fields uses a comprehensive approach in the design of any technical object. It combines the requirements and their integration into all subsystems of the technical object. This approach, which is described by the VDI 2006 norm, can generally be used in the suggestion of regulation for the pressure pipe networks.
Ranking objects is an essential problem in recommendation systems. Since comparing two objects is the simplest type of queries in order to measure the relevance of objects, the problem of aggregating pair wise comparisons to obtain a global ranking has been widely studied. In order to learn a ranking model, a training set of queries as well as their correct labels are supplied and a machine learning...
Recent surveys show that there is enormous increase of organizations intending to adopt cloud, but one of their major obstructions is the trustworthiness evaluation of cloud service candidates. Performing evaluations of cloud service candidates is expensive and time consuming, especially with the breadth of services available today. In this situation, this paper proposes a novel trustworthiness measurement...
Fluid mechanics considers two frames of reference for an observer watching a flow field: Eulerian and Lagrangian. The former is the frame of reference traditionally used for flow analysis, and involves extracting particle trajectories based on a vector field. With this work, we explore the opportunities that arise when considering these trajectories from the Lagrangian frame of reference. Specifically,...
The conventional Takagi-Sugeno (T-S) fuzzy model is an effective tool used to approximating behaviors of nonlinear systems on the basis of precise and certain input and output observations. In some situations, however, we can only obtain mixture of precise data (for input variables), imprecise and uncertain data (for output variable/response). This paper presents a method used to constructing T-S...
This paper presents a real-time human action recognition method based on a modified Deep Belief Network (DBN) model. To recognize human actions, the positions of human joints are taken into account. Each action is made of a sequence of human joint positions. Since the classic DBN cannot deal with temporal information, the proposed method employs the conditional Restricted Boltzmann Machine (cRBM)...
An update algorithm of least squares support vector machine (LSSVM) is proposed to tackle the time-varying characteristics of the real industrial process. The process variations are concluded to two categories, and accordingly the samples adding and samples replacement are proposed to update the initial LSSVM model incrementally. Then the LSSVM model with proposed updating measures is applied in the...
The inconsistent diagnostic information often occurs in fault diagnosis of complex equipments. In order to improve the diagnosis precision, an integrated fault diagnosis method is proposed based on variable precision rough set (VPRS) and Naive Bayesian network classifier (NBNC). Firstly, according to the relative discernibility of the original fault diagnosis decision table, the β in VPRS is self-determined...
The aim of this paper is to advance the smoothing of original data sequence. According to the theory of prior using of new information, based on the present theories of buffer operators and some already existed weakening buffer operators, some new weakening buffer operators are established.They are compared with the existing weakening buffer operators in effectiveness.The problem that there are some...
It is difficult to get satisfactory churn prediction results by traditional models, because the available customer samples in target domain are usually few and the class distribution of customer data is imbalanced. This study proposes a group method of data handling (GMDH) based dynamic transfer ensemble (GDTE) model for churn pre-diction. It first transfers the data in related source domains to the...
In view of the problem that currently the students choose online test questions blindly, the establishment of the item recommendation system is necessary. According to the student's level, an estimating algorithm is used to sort items and recommend the question which is in the front of the sort to the student. According to the study of student over a certain period of time and all the answers to the...
Automatic classification of texts by topic is a well-studied problem. Nonetheless, classifying twitter messages by topic is difficult because the messages are short and the features space for classification is very sparse. We propose a method to enhance the text of the messages that contain links with external information such as the title of the web pages, and with the most frequent terms from these...
Due to the non-liner, poor selectivity and cross-sensitivity of the combustible gas in the sewer, an analysis prediction model of the combustible gas in the sewer has been established based on the PSO-SVR machine, the model has introduced a new particle swarm algorithm to support the vector regression machine so that it can optimize the important parameters, realizing the automatic determination of...
Among many applications of Shuttle Radar Topography Mission (SRTM) and digital elevation model (DEM), the suitability of this data for simulating potential insolation (PI) has not been fully examined. This study examined the accuracy of potential insolation simulation based on 3 arc-second resolution SRTM. The National Elevation Dataset (NED) was used as reference data. Using a method which does not...
POI updates have a direct influence on data up-to-date state, thereby affecting the data value of POI. Aimed at solving the problem facing POI rapid and accurate update, an update approach for POI based on Weibo check-in data is brought forward in this paper. Firstly, regarding to the quality issue of check-in data, a pre-processing approach with spatial registration is proposed. Then, a POI data...
In this paper, we propose a new virtual support to assist postgraduates through the Graduate Virtual Research Environment (GVRE). The virtual support will provide a 24 hour answering servicing for postgraduate students relating to their PhD journeys, for example, advice needed regarding “what is needed for your first 6 month Upgrade report”. The assisted learning mechanism found within the GVRE will...
Classification of low back disorders (LBDs) risks for common industrial lifting jobs is important to control and prevention of this common disability. Of particular interest to the researchers is the use of data mining methods in risk classification. This paper presents an adaptive neuro-fuzzy inference system (ANFIS) model for classifying LBDs risks. Though neuro-fuzzy inference modeling is extensively...
Mining data streams has attracted the attention of the scientific community in recent years with the development of new algorithms for processing and sorting data in this area. Incremental learning techniques have been used extensively in these issues. A major challenge posed by data streams is that their underlying concepts can change over time. This research delves into the study of applying different...
Accidental releases and improper disposal of hazardous chemicals has led to widespread chemical contamination of subsurface soils and water-bearing formations. Effective remediation and restoration of such contaminated sites is dependent upon knowledge of the contaminant's mass and distribution within the aquifer. Recent research has shown that the estimation of certain metrics which summarize the...
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